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jev-paint

achimala/jev-paint

Paint images by having Jev predict each pixel's colour.

Automated README summary

Automatically summarized from the README on 20 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A local browser app that turns Jev's pixel probability distributions into paintings. Aimed at people with a TypeSafe Jev API key who want to run a small creative experiment on their own machine.

How it uses Jev

For each pixel location on the chosen grid, the app sends typed questions about palette or HSL/RGB channels and asks Jev for calibrated probabilities. Four concurrent batches are validated, then spatially correlated categorical sampling picks stroke pigments, mean colour supplies the underpainting, and entropy controls relief.

Primitives:choicescore

Technique worth stealing

Use per-pixel Jev probabilities as sampling weights, letting predicted confidence decide stroke width, then combine independent channel probabilities into a painting.

Try it

Run `python3 server.py`, open http://127.0.0.1:8791, paste your Jev API key, pick a representation and grid, then enter a prompt.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectunclear0.51
  • Shows a System One patternFound in material0.65
  • Describes handling uncertaintynot found in the excerpt0.06
  • Reports measured numbersnot found in the excerpt0.04
  • Is a runnable toolFound in material0.93
  • Top-10 learning shortlist signalunclear0.43
  • Is a replica of the modelnot found in the excerpt0.03
  • Solves a common problem (0–2)score on a 0–2 scale0.00 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.51Shows a System One pattern0.65Describes handling uncertainty0.06Reports measured numbers0.04Is a runnable tool0.93Top-10 learning shortlist signal0.43Is a replica of the model0.0300.51Solves a common problem (0–2)0.00 / 2012

no-judgment band (0.40–0.60)

Design patterns
Scorecard0.88Questionnaire0.52Inspection0.3400.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.